Forest Fire Detection & Distance Estimation System

This repository contains the implementation code for a camera-based forest fire detection and distance estimation system.  
It is shared for viewing and reference purposes only — the model and dataset are not included.

This project is an AI-powered Forest Fire Detection and Distance Estimation System that detects fire in real-time camera feeds and estimates its distance from the camera without additional hardware.

For View: Click Any

System Screen:

Real Time:

The system uses:

• YOLOv8 for fire detection.
• Perspective Grid Mapping for distance estimation using only camera parameters.

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🔥 Features

• Real-time fire detection using a deep learning model.
• Distance estimation based on camera height and tilt angle.
• Works with standard CCTV, drone, or surveillance cameras.
• Designed for low-cost deployment without LiDAR or radar.

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✨ Uniqueness

• Wide range distance estimation not using any traditional harware.

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🛠️ Tech Stack

• Python 3
• YOLOv8 (Ultralytics)
• OpenCV (image processing & perspective mapping)
• NumPy (matrix & math operations)
• Jupyter Notebook (app.ipynb)

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📂 Repository Structure

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├── app.ipynb              # Main notebook with fire detection & distance estimation logic
├── README.md              # Project documentation
└── requirements.txt       # Python dependencies

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⚠️ Important Notes

• This repository does NOT contain:
  • Trained YOLOv8 fire detection model (.pt file)
  • Grid calculation dataset
• Without these files, the notebook cannot be executed — it is intended only for reading and reference.

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🖼️ System Workflow

1. Camera Calibration – Input camera height and tilt angle.
2. Fire Detection – YOLOv8 model detects flames in the video feed.
3. Distance Estimation – Perspective mapping calculates approximate distance.

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📜 License

This project is shared for educational and research viewing only.

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👤 Author

Sowndappan S Email: santoshsowndappan@gmail.com

Mythili S

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